[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation 事件

[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation arXiv:2605.25821v1 Announce Type: new Abstract: Vision-Language Models such as CLIP exhibit strong zero-shot recognition capability by aligning images with textual concepts, yet they often underperform on multi-label recognition where multiple objects co-exist. A key bottleneck is that the [CLS] token, as a single global visual representation, is insufficient to faithfully encode diverse targets with